Garbage in, garbage out

Garbage in, garbage out (GIGO) in the field of computer science or information and communications technology refers to the fact that computers, since they operate by logical processes, will unquestioningly process unintended, even nonsensical, input data ("garbage in") and produce undesired, often nonsensical, output ("garbage out").

Contents

It was most popular in the early days of computing, but applies even more today, when powerful computers can produce large amounts of erroneous information in a short time. The first use of the term has been dated to a 1 April 1963 syndicated newspaper article about the first stages of computerization of the US Internal Revenue Service.[1] The term was brought to prominence as a teaching mantra by George Fuechsel,[2] an IBM 305 RAMAC technician/instructor in New York. Early programmers were required to test virtually each program step and cautioned not to expect that the resulting program would "do the right thing" when given imperfect input. The underlying principle was noted by the inventor of the first programmable computing device design:

On two occasions I have been asked, "Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?" ... I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.

The term can also be used as an explanation for the poor quality of a digitized audio or video file. Although digitizing can be the first step in cleaning up a signal, it does not, by itself, improve the quality. Defects in the original analog signal will be faithfully recorded, but may be identified and removed by a subsequent step by digital signal processing.

Trust

Garbage in, gospel out is a more recent expansion of the acronym. It is a sardonic comment on the tendency to put excessive trust in "computerised" data, and on the propensity for individuals to blindly accept what the computer says. Since the data go through the computer, people tend to believe them:

Decision-makers increasingly face computer-generated information and analyses that could be collected and analyzed in no other way. Precisely for that reason, going behind that output is out of the question, even if one has good cause to be suspicious. In short, the computer analysis becomes a credible references point although based on poor data.[4]

Decision-making

GIGO is also commonly used to describe failures in human decision-making due to faulty, incomplete, or imprecise data.